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Impact and interplay of $\Lambda$CDM analysis choices for LSST cosmic shear
Cosmology and Nongalactic Astrophysics · Submitted 25 Feb 2026
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim Adopting literature measurements of the reduced redshift calibration precision found from galaxy cross-correlation techniques, combined with current levels of baryon feedback uncertainty, we forecast final year LSST cosmic shear constraints that barely improve upon the first year analysis.
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We forecast cosmological parameter constraints for a cosmic shear analysis of the Rubin Observatory Legacy Survey of Space and Time (LSST), defining an analysis framework that can accurately recover the $\Lambda$CDM model in the presence of astrophysical and data-related systematics. When accounting for our present uncertainty on the suppression of the non-linear matter power spectrum through baryon feedback, we find that the error on the composite parameter $S_8=\sigma_8\sqrt{\Omega_{\rm m}/0.3}$ almost doubles compared to an LSST analysis which neglects this astrophysical phenomenon. After the first year of observations, LSST will extend beyond the magnitude limit of existing representative spectroscopic calibration samples, requiring photometric redshifts to be calibrated using an alternative strategy. Adopting literature measurements of the reduced redshift calibration precision found from galaxy cross-correlation techniques, combined with current levels of baryon feedback uncertainty, we forecast final year LSST cosmic shear constraints that barely improve upon the first year analysis. This forecast therefore serves as encouragement to the community to develop methodology and observations to constrain models of baryon feedback and enhance photometric redshift calibration at depths where spectroscopy is unrepresentative. With tight priors on both these systematic terms, we forecast that LSST cosmic shear can deliver constraints on $S_8$ that are more than five times as constraining as existing cosmic shear surveys.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | We forecast cosmological parameter constraints for a cosmic shear analysis of the Rubin Observatory Legacy Survey of Space and Time (LSST), defining an analysis framework that can accurately recover the $\Lambda$CDM model in the presence of astrophysical and data-related systematics. | contribution 0.98 | 0.86 | 0.12 | asserted 0.97 |
| s1 | When accounting for our present uncertainty on the suppression of the non-linear matter power spectrum through baryon feedback, we find that the error on the composite parameter $S_8=\sigma_8\sqrt{\Omega_{\rm m}/0.3}$ almost doubles compared to an LSST analysis which neglects this astrophysical phenomenon. | result 1.00 | 0.88 | 0.20 | asserted 1.00 |
| s2 | After the first year of observations, LSST will extend beyond the magnitude limit of existing representative spectroscopic calibration samples, requiring photometric redshifts to be calibrated using an alternative strategy. | background 0.88 | 0.12 | 0.04 | asserted 0.98 |
| s3 | Adopting literature measurements of the reduced redshift calibration precision found from galaxy cross-correlation techniques, combined with current levels of baryon feedback uncertainty, we forecast final year LSST cosmic shear constraints that barely improve upon the first year analysis. | result 0.99 | 0.77 | 0.32 | asserted 0.95 |
| s4 | This forecast therefore serves as encouragement to the community to develop methodology and observations to constrain models of baryon feedback and enhance photometric redshift calibration at depths where spectroscopy is unrepresentative. | future work 0.98 | 0.30 | 0.40 | asserted 0.69 |
| s5 | With tight priors on both these systematic terms, we forecast that LSST cosmic shear can deliver constraints on $S_8$ that are more than five times as constraining as existing cosmic shear surveys. | result 0.94 | 0.79 | 0.25 | asserted 0.76 |
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The paper
Original abstract
We forecast cosmological parameter constraints for a cosmic shear analysis of the Rubin Observatory Legacy Survey of Space and Time (LSST), defining an analysis framework that can accurately recover the $\Lambda$CDM model in the presence of astrophysical and data-related systematics. When accounting for our present uncertainty on the suppression of the non-linear matter power spectrum through baryon feedback, we find that the error on the composite parameter $S_8=\sigma_8\sqrt{\Omega_{\rm m}/0.3}$ almost doubles compared to an LSST analysis which neglects this astrophysical phenomenon. After the first year of observations, LSST will extend beyond the magnitude limit of existing representative spectroscopic calibration samples, requiring photometric redshifts to be calibrated using an alternative strategy. Adopting literature measurements of the reduced redshift calibration precision found from galaxy cross-correlation techniques, combined with current levels of baryon feedback uncertainty, we forecast final year LSST cosmic shear constraints that barely improve upon the first year analysis. This forecast therefore serves as encouragement to the community to develop methodology and observations to constrain models of baryon feedback and enhance photometric redshift calibration at depths where spectroscopy is unrepresentative. With tight priors on both these systematic terms, we forecast that LSST cosmic shear can deliver constraints on $S_8$ that are more than five times as constraining as existing cosmic shear surveys.
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References
How the literature uses it
2 arXiv papers cite this in 3 sentences
What it cites · 42 sentences without a confident label
Contests 1 paper
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This clear result is, however, in stark contrast to the LSST forecasts of [ref] who find that baryon feedback contributes just 1% to their total error budget.
Machine Learning LSST 3x2pt analyses -- forecasting the impact of systematics on cosmological constraints using neural networks · Joint Constraints in $w_0-w_a$CDM · contest 0.71
Uses the method or tool of 2 papers
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For our fiducial analysis we adopt to model the non-linear matter power spectrum [ref] , including the free parameter $Θ_AGN$ to modulate the strength of the baryon feedback suppression[$Θ_AGN$ is an internal parameter of , related to the AGN heating parameter in the BAHAMAS simulations as $Θ_AGN=log_10(ΔT_heat/K)$.
HMcode-2020: Improved modelling of non-linear cosmological power spectra with baryonic feedback · Fiducial analysis with · 1.00
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Following [ref] , we conduct a joint analysis that includes cosmic shear data to an $ℓ_max=5000$ and marginalises over our uncertainty.
Machine Learning LSST 3x2pt analyses -- forecasting the impact of systematics on cosmological constraints using neural networks · Joint Constraints in $w_0-w_a$CDM · 0.95
Uses data or values from 2 papers
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There are a range of observational constraints on this parameterisation of baryon feedback, with [ref] using a cross-correlation analysis of weak lensing and the thermal SZ effect finding $Θ_AGN = 7.96^+0.2_-0.48$ and [ref] using the cross-correlation between cosmic shear from DES-Y3 with ROSAT X-ray data (hereafter DESxROSAT) to constrain $Θ_AGN=7.998±0.008$.
X-Ray-Cosmic-Shear Cross-Correlations: First Detection and Constraints on Baryonic Effects · Fiducial analysis with · 0.94
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Using measurements of the three-dimensional matter power spectrum, $P_mm(k,z)$ [ref] , we take the ratio between the `L1$_$m9' hydrodynamical simulation and the corresponding gravity-only simulation as our feedback suppression model.
The FLAMINGO project: Baryon effects on the matter power spectrum · Building mock data using FLAMINGO · 0.85
Compares with 3 papers
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As such we can understand the differing conclusions between this study and [ref] .
Machine Learning LSST 3x2pt analyses -- forecasting the impact of systematics on cosmological constraints using neural networks · Joint Constraints in $w_0-w_a$CDM · 0.95
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Using a deconvolution approach to account for noise-, model-, and detection-related bias, combined with deep data from the LSST Deep Drilling Fields, this method has been shown to deliver a shear accuracy that is better than $σ_m < 0.001$ [ref] .
Deep-field Metacalibration · Data-related systematics · 0.84
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It is also pessimistic compared to the accuracy forecasted for the DESC-adoped Metadetection technique [ref] .
Mitigating Shear-dependent Object Detection Biases with Metacalibration · Data-related systematics · 0.98
Cites as support 10 papers
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This result would nominally motivate the use of TATT as the default, but [ref] and [ref] demonstrate how without tight priors on the photometric redshift calibration uncertainty, weakly constrained TATT parameters can absorb errors in the redshift distribution leading to a bias on the derived cosmological parameters.
Redshift requirements for cosmic shear with intrinsic alignment · Varying the intrinsic alignment model · 0.97
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This result would nominally motivate the use of TATT as the default, but [ref] and [ref] demonstrate how without tight priors on the photometric redshift calibration uncertainty, weakly constrained TATT parameters can absorb errors in the redshift distribution leading to a bias on the derived cosmological parameters.
Photometric redshifts and intrinsic alignments: degeneracies and biases in 3$\times$2pt analysis · Varying the intrinsic alignment model · 0.97
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Observational evidence supports these more extreme models in the form of cross-correlation studies of weak lensing with either measurements of the thermal Sunyaev-Zel'dovich (SZ) effect [ref] , or the diffuse X-ray background [ref] , along with joint analyses of lensing with the kinetic-SZ effect [ref] .
X-Ray-Cosmic-Shear Cross-Correlations: First Detection and Constraints on Baryonic Effects · Introduction · 0.98
Cites as background 2 papers
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There are many alternative approaches to using to model baryon feedback including: calibrated baryonification models [ref] , updated hydrodynamical simulation-informed halo models [ref] , along with emulators, some of which are created using machine learning techniques [ref] .
2509.01881 · Fiducial analysis with · 0.98
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Cosmic shear measures the observed lensing-induced correlation between galaxy shapes as a function of redshift, mapping both the growth of large-scale structures and the expansion history of the Universe [ref] .
Growth of Cosmic Structure · Introduction · 1.00
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